Object Authentication

ABSTRACT

A device detects multi-spectral imaging by using scan elements. The device may include an illumination module and a detection module to detect light scattered from an object illuminated by the illumination module. The device may also include an array of light sources to produce light at a plurality of different wavelengths, and create a line of illumination with each of the different wavelengths. The light detection may be applied to authenticate and validate documents, such as banknotes moving along a document conveyer.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 14/024,074 filed on Sep. 11, 2013, published asU.S. 2014/0009752 A1 and entitled “Object Authentication,” which is acontinuation of and claims priority to U.S. patent application Ser. No.13/487,442 issued as U.S. Pat. No. 8,547,537 which is a continuation ofand claims priority to U.S. patent application Ser. No. 12/904,908issued as U.S. Pat. No. 8,194,237, which claims benefit to U.S.provisional application serial No. 61/251,915, filed on Oct. 15, 2009,all of which are incorporated herein by reference in their entirety.

TECHNICAL FIELD

This invention relates in general to authentication of a document, andmore particularly, to characterizing a document from scattered lightgenerated from a multi-spectral light source.

GENERAL INFORMATION

Viewing and analyzing a document with the naked eye is limited by humanconstraints and human error. Spectroscopy uses light and sensors to viewobjects that a human cannot see and/or in a manner that a human cannotperform in a reasonable amount of time. For example, for the purposes ofacquiring a multi-spectral image of a document, multiple wavelengths oflight impinge upon a document. A portion of the incident light maypropagate through the document, a portion of the light may be absorbedby the document or its printed inks, and a portion may be scattered backor reflected from the document. Generally, a measurement of the lightscattered from the surface of the document is utilized, and may in turnbe used to confirm the document authenticity.

A number of methods may be utilized for acquiring a multi-spectral imageof a document. In operation, a variety of light sources, filters,selective detectors, and optical arrangements may be used to createproper illumination and imaging conditions for acquiring such data.However, with respect to acquiring images of high-speed moving objectswithin a confined space, such as on a high-speed document transportdevice, these methods may face additional challenges. The capture ofwell-resolved images both spectrally (number of wavelengths imaged) andoptically (pixel resolution) begs for a robust arrangement of imagingresources.

One approach for imaging in such moving conditions is line scan (alsoreferred to as “pushbroom”) imaging. Line scan imaging uses a one- ortwo-dimensional sensor to capture a two-dimensional (“2D”) image of themoving object. Line scan imaging may be performed by using one or morelines of sensor pixels. In operation, the second dimension results fromthe motion of the object with respect to one or more detectors, andsubsequent “stitching” of the one-dimensional data together is performedto create a composite image. An image of finite length is thereforecaptured line-by-line by the detector(s) and may be assembled viacomputer processing.

Another approach to high-speed imaging may include the use of a largetwo-dimensional array and imaging the target onto that array. Underthese conditions, a very bright light source is used to illuminate theentire area, and the image is captured quickly before the motion of theobject induces blur or other resolution reducing problems develop.Alternatively, a portion of the array could be used and multipletwo-dimensional images could be stitched together to create a singleimage similar to the “stitching” of a line scan image.

Multi-spectral imaging of an object adds further complexity. Forexample, for each image taken, the challenges of line scan imaging andtwo-dimensional imaging may be further complicated by creating images ateach light wavelength of interest. For line scan imaging, multiple linesof illumination are created and/or multiple sensors of differentspectral sensitivity are implemented to capture images, which are“stitched” together in physical (2D) space, and registered in wavelengthspace as well. For two-dimensional areas, the utilization of brightillumination and high-speed acquisition are further complicated byhaving to perform these operations for all wavelengths of interestbefore the object moves out of view.

In general, there are a number of ways of illuminating a document.Except in the case of transmission illumination, these illuminationtechniques affect the ability to collect light at the detector ordetectors. In general, the space adjacent to a document is sharedbetween the mechanisms for illumination and detection. As this physicalspace is limited, so too may be an ability to collect and/or illuminatethe document being examined.

One technique of illumination is “epi-illumination” in which the lightperpendicularly impinges upon the document, and the scattered light fromthe document travels back along the same path for some distance. Thisillumination procedure necessitates, to some degree, either blockingsome portion of the collected light, or an overall reduction in thetotal collected efficiency. Techniques utilized for such illuminationmay be implemented by using partially silvered mirrors or polarizingbeam splitters.

Another illumination technique is shared numerical aperture(“shared-NA”), or grazing illumination, where the illumination isincident at an angle to the document, which can limit the collectionangle of the optical detection mechanism. “Shared-NA” refers to aprocess of using the space around a sample and the optics, and the “NA”is the cone of light originating from the field of view and beingcollected by the optical system. For the most efficient light collectionpossible, one may desire to use all of this NA light. The less collectedlight and the less brightness used, the worse the detected signal. Theact of “sharing NA” means that a portion of the ability to collect lightis sacrificed to illuminate better. Unlike epi-illumination, little ornone of the same optical path is shared and hence does not require a“splitting” mechanism. The choice between these two illuminationtechniques may be determined by the distance to the object and therequired optical illumination or collection efficiency.

A document may be illuminated in either a structured or unstructuredmanner. An example of unstructured illumination is a lamp in which itslight directly impinges the document. A problem with such unstructuredillumination is its inherent low efficiency, since only a small portionof the source light reaches the document of interest, resulting insignificant portion of the light effectively wasted. This inefficiencyis undesirable because it may increase power usage, may increase heat(which may lead to many electronic or thermal dissipation problems), andmay increase relative noise (less light may mean less signal-to-noise).

Structured illumination, however, is often more efficient at collectingand directing the source light to the document of interest. As a result,less heat is generated, and less power is used to illuminate thedocument of interest. Multi-spectral imaging often requires multiple,independently-controlled light sources spatially offset from oneanother. To create equal illumination of the regions of interest in thedocument, it may be necessary to slightly redirect each illuminationsource to compensate for this spatial offset, which is generally notpossible with a single, unstructured light source.

Solid-state light sources, such as light emitting diodes (“LEDs”) ordiode lasers, may be used. Structured illumination effectively collectsand directs these light sources to the document of interest using themost effective spatial distribution. Depending upon the arrangement ofdetection optics and detector arrays, different structured illuminationdistribution schemes might be used to provide an optimal lightingconfiguration.

Line scan imaging may utilize a single line of structured illuminationacross the target so that it just “overfills” the area to be imaged bythe detection optical system; any greater area of illumination would belost and an inefficient use of light. One configuration of line scanillumination may be a set of cylindrical optics, which have zero powerto condense the light in the extrusion direction, but can havesignificant optical power in the orthogonal direction. By modifying thepower of the cylindrical lens(es), one can control the magnification inthe orthogonal direction. For example, a 100 mm long array of 300 micronwide LEDs can form a line of illumination approximately 100 mm long and3 mm wide if a cylindrical optical configuration of 10× magnification isused. This configuration results in a controlled magnification of thelight source in the orthogonal direction while blurring the illuminationalong the line of illumination. This blurring may be advantageous ifdifferent LEDs are placed in a linear array to obtain a more uniformdistribution of the light. There are other mechanisms to form a line oflight, including commercially available one-dimensional diffusers, whenused with collimated light sources, such as lasers.

An optical configuration that images the line of illumination back tothe array of detectors may utilize a conventional imaging approach usingspherical as opposed to cylindrical lenses. The cylindrical lenses maybe used to form the illumination of the sample and not for the imagingaspect.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example sensor system, according to exampleembodiments of the present invention.

FIG. 2 illustrates an example detected image, according to exampleembodiments of the present invention.

FIG. 3 illustrates an example block diagram, according to exampleembodiments of the present invention.

FIG. 4 illustrates an example set of images, according to exampleembodiments of the present invention.

FIG. 5 illustrates an example pixel and wavelength diagram based on anexamined document, according to example embodiments of the presentinvention.

FIG. 6 illustrates an example light concentration and relatedcalculation used to produce a detected image, according to exampleembodiments of the present invention.

FIG. 7 illustrates an example configuration of an illuminator module,according to example embodiments of the present invention.

FIG. 8 illustrates example paths of light traveling through anilluminator module, according to example embodiments of the presentinvention.

FIG. 9 illustrates an example LED array configuration, according toexample embodiments of the present invention.

FIG. 10 illustrates an example LED array configuration, according toexample embodiments of the present invention.

FIG. 11 illustrates an example detector configuration, according toexample embodiments of the present invention.

FIG. 12 illustrates an example detector layout, according to exampleembodiments of the present invention.

FIG. 13 illustrates an example optics barrel, according to exampleembodiments of the present invention.

FIG. 14 illustrates an example light ray trace, according to exampleembodiments of the present invention.

FIG. 15 illustrates an example flow diagram, according to exampleembodiments of the present invention.

FIG. 16 illustrates an example image data organization configuration,according to example embodiments of the present invention.

FIG. 17 illustrates an example sensor configuration, according toexample embodiments of the present invention.

FIG. 18 illustrates an example light wavelength diagram, according toexample embodiments of the present invention.

FIG. 19 illustrates an example computer entity configured to performoperations disclosed in various embodiments of the present invention.

FIG. 20 illustrates a flow diagram of an example method, according toexample embodiments of the present invention.

FIG. 21 illustrates an example of multiple illumination bands used toproduce images of a document, according to example embodiments of thepresent invention.

FIG. 22 illustrates an example table of modulation codes, according toexample embodiments of the present invention.

FIG. 23 illustrates an example photodiode signal, according to exampleembodiments of the present invention.

FIG. 24 illustrates an example photodiode signal, according to exampleembodiments of the present invention.

DETAILED DESCRIPTION

It will be readily understood that the components of the presentinvention, as generally described and illustrated in the figures herein,may be arranged and designed in a wide variety of differentconfigurations. Thus, the descriptions of the embodiments of the presentinvention, as represented in the figures, is not intended to limit thescope of the invention as claimed, but is merely representative ofselected embodiments of the invention.

The features, structures, or characteristics of the invention describedthroughout this specification may be combined in any suitable manner inone or more embodiments. For example, the usage of the phrases “exampleembodiments,” “some embodiments,” or other similar language, throughoutthis specification refers to the fact that a particular feature,structure, or characteristic described in connection with the embodimentmay be included in at least one embodiment of the present invention.Thus, appearances of the phrases “example embodiments,” “in someembodiments,” “in other embodiments,” or other similar language,throughout this specification do not necessarily all refer to the samegroup of embodiments, and the described features, structures, orcharacteristics may be combined in any suitable manner in one or moreembodiments.

Embodiments of the present invention provide a document authenticationsensor that detects features, characteristics, and attributes ofdocuments, including, but not limited to, banknotes and drafts. Theremainder of the description exemplifies applications related tobanknotes and related examples. However, such image capturingconfigurations may be applicable to any document, including, but notlimited to, identification credentials, security labels, packaging, orany surface that may be authenticated with multi-spectral imaging.Furthermore, embodiments of the present invention are not to be limitedto documents, but may be applicable to any target or object that can beimaged in accordance with such embodiments. The image capturing sensormay perform certain operations to determine the presence and/orauthenticity of a spectrally unique feature present in banknotes, thedenomination of banknotes, and/or the presence of multiple banknotes.

According to example embodiments of the present invention, line scanimaging may be used to produce a line of illumination that is spatiallyswept relative to an object (e.g., a document) to be characterized, suchas for purposes of authentication, and resultant scattered and/orreflected light is then sensed or captured by a linear detector. Due tothe relative motion between the optics and the object, multiplesequential line images build up to form the captured image. Thisconfiguration provides an ability to form images or multi-spectral imagestacks of fast moving items, such as banknotes or manufactured items,such as transported by or on a moving conveyer. The terms “image” and“images” are used herein to refer to data collected as a result of thedetection of light energy scattered, reflected, and/or filtered by atarget object, which resulted from illumination of the target object byone or more light sources. It is not necessary that such “images” beeither visible or displayed on a display device, though for purposes ofdescribing embodiments of the present invention, one or more figuresreferenced herein may illustrate such an “image” or “images.” Herein,the terms “scattered” and “reflected” may be used interchangeably todescribe the light received by detectors, emanating from the targetobject as it is illuminated by one or more light sources. As disclosedherein, an “image” may be comprised of “pixels,” which essentiallyidentify a predetermined location of a predetermined size (area) on theobject being examined.

A multi-spectral image stack is characterized by a collection of imagesof the target object of interest, which are collected under differentillumination conditions. These different illumination conditions may becharacterized by each image generated by scattered light as a result ofillumination from a light source of a different wavelength and/orcollection of light of different wavelengths.

An approach to overcome the limited spectral bandwidth of a singledetector array is to interlace different detectors of different spectralsensitivities in the same array. However, this approach may degrade theoverall spatial resolution in the direction of the array. It alsorequires some degree of interpolation as the different types ofdetectors are spatially separate from each other.

Another technique may include multiple linear arrays of different typesof detectors. In this technique, two (or more) parallel lines ofillumination are formed at the sample by two (or more) linear arrays ofLEDs. The linear arrays of LEDs may each use a set of cylindricaloptics. Similarly, this configuration may be simplified by using only asingle set of cylindrical optics, which may result in cost reduction ofthe illumination optical system, reduced difficulty of alignment, and/orensuring that the two lines of illumination are parallel and separatedby the correct distance.

An alternative technique may include multiple linear arrays with thesame type of detector, such as silicon, where each linear array has beenfiltered, for example, with red, green, and blue filters. This allowsfor a color image reconstruction, or multi-spectral reconstruction ifmore than three arrays are used. The use of multiple arrays may allowmore image acquisitions to occur in the same periods of time, thusallowing the use of more wavelengths for superior spectral resolution.

Example embodiments of the present invention disclose combinations ofoptical component arrangements and signal processing to enablehigh-speed multi-spectral line scan imaging. Examples may includeoptimized implementations of forming structured illumination by a lineararray of LEDs having different wavelengths in accordance with acylindrical optics illumination.

Example embodiments may provide an illumination configuration thatincludes a linear array of LEDs, where each of at least a plurality ofthe LEDs produces a different wavelength of light. Further details ofthe illumination configuration may include each of at least a pluralityof the LEDs being independently controlled (e.g., modulated), orcontrolled in various sets or groups of multiple LEDs. For example,certain multiples of the same LED wavelength may be uniformly spacedalong the array a predefined distance apart. As further described indetail herein, the illumination may be modulated according to a timereference created within the sensor that allows correlation betweenillumination conditions and the detector output.

As further described in detail herein, on the detection side of thesensor configuration, an arrangement of detector elements may be formedto allow simultaneous imaging of multiple sets of wavelengths to collecta larger set of wavelengths within limited time and space budgets. Thestructured illumination and detection arrays may be coupled through anoptical system that images the multiple sets of wavelengths on theappropriate multiple sets of detection elements. The multi-spectralimages may be created from the detector data by “stitching” together theappropriate data based on time references, or another technique, used inthe acquisition process to create a spatially and spectrally resolvedmulti-spectral image stack.

According to example embodiments of the present invention, two lineararrays of LEDs form two lines of illumination at the target document,which are imaged back to two linear arrays of detectors. One line ofillumination contains a first set of wavelengths that are sensed by thefirst array of detectors, and the other line of illumination contains asecond set of wavelengths that are sensed by the second array ofdetectors. By use of time-division multiplexing (“TDM”) of the differentLEDs, or other illumination techniques such as direct sequence spreadspectrum modulation (“DSSSM”), as further described in detail herein, amulti-spectral array of images spanning multiple detector spectralranges may be formed. The use of additional lines of illumination andarrays of detectors may also be used to further extend the spectralrange.

The above-noted approaches to image acquisition may not reduce thelateral spatial resolution that a single array of different interpolateddetectors would produce. However, it utilizes a known relative motion,as these arrays of detectors are laterally spaced. To reconstruct thefull image, the speed of relative motion and the separation distancebetween the arrays may be used to digitally “shift” the different lineararrays to be co-linear once each portion has been detected. Therefore,multi-spectral images of high optical and spectral resolution areobtained in a very small form factor.

Referring to FIG. 1, embodiments of a sensor system comprise threesubsystems, for example, an upper sensor housing (“USH”) 101, a lowersensor housing (“LSH”) 102, and an external processor module (“EPM”)103. The external processor module 103 may reside at a remote location,or the EPM 103 may be co-located with the USH 101 and LSH 102.

Authentication operations as well as other imaging-based measurements,such as determination of the note denomination, facing, orientation,etc., may be performed by a back-scatter imaging mode of the sensorsystem. In this back-scatter mode of operation, light is transmittedfrom an illuminator module 104, strikes (impinges) a surface of thebanknote 100, and reflected light is scattered back into the housing(either or both of the USH 101 and LSH 102), through the optics 105, andonto a housing's detector module 106.

The above-noted procedure of transmitting light towards the banknote 100may be performed on both sides of the banknote 100 as illustrated in theupper sensor housing 101 and the lower sensor housing 102. The resultsobtained by the upper sensor housing 101 and the lower sensor housing102 are forwarded to the EPM 103 for processing. In FIG. 1, the pathstraveled by the light waves within the upper sensor housing 101 aregenerally indicated by the dashed line; the paths traveled by the lightwaves within the lower sensor housing 102 are generally indicated by thedotted line.

A spatial detector resolution of the sensor system may be limited by thenumber and spacing of the detection elements (sensors) in the detectormodule 106, or by the inherent optical resolution of the optics 105,whichever is poorer. For example, a detector spacing of 2 micronscenter-to-center between the detector sensors may be unnecessary if theoptical system has a 100 micron blur spot.

Assuming that an engineered optical design permits a desired detectorspacing to be implemented, there are other considerations, such as thespeed of the sensor system. For example, existing off-the-shelfdetectors/sensors have an advantage of multiple detectors/sensorslocated within a very small pitch (e.g., on the order of 1 micron), butonly have a single or a few read-out element(s) that convert theelectrical signals from each of the many detectors/sensors to a streamof digital data. This read-out conversion may have a maximum data ratethat limits the overall processing speed of the detector module 106.

Alternatively, a custom detector array may have many digitizingelements, allowing up to one digitizer per element. This significantlyincreases the throughput of the array, however, these detector elementsmay be much larger (e.g., on the order of 100-1000 microns). This maysignificantly limit the spatial resolution. A third alternative is afully customized detector array, which may have many tiny detectorelements (e.g., with a resolution of 10 microns) and many digitizingelements, which allows for both increased processing speed and imagingresolution.

The back-scattered image collected by each sensor housing 101, 102 maybe a multi-spectral stack of two-dimensional images of the surface ofthe banknote 100 with a predefined resolution (e.g., 1 mm). However,lower and higher resolutions are within the scope of the presentinvention. FIG. 2 illustrates an example of a banknote 100 sampled witha 1 mm pixel resolution, according to example embodiments of the presentinvention. The spectral resolution of the detected image may varydepending on various factors. The illumination elements used in theilluminator module 104 may be selected from very narrow opticalfrequency sources, (e.g., lasers and moderate spectral width sourcessuch as LEDs), or broad optical frequency sources (e.g., lamps).

The spectral resolution may also be controlled through the use ofcertain detectors included in the detector module 106. The detectors maybe selected based on a target light wavelength. One example of such adetector may be a filtered photodiode. Certain filters may be used toallow any set of wavelengths to be passed on to the detector. Thisspectral resolution may vary over the range of wavelengths to beinvestigated.

An example of targeted wavelengths is illustrated in FIG. 18, whichshows a first set of relatively narrow wavelengths “A” that may be usedin the visible region, for example to accurately determine the color ofa banknote's ink. A second set of wavelengths “B” of broader frequenciesmay be used in an infrared (“IR”) region to determine an absence orpresence of IR transparency.

Referring to FIG. 3, as noted above with respect to FIG. 1, the upperand lower housings 101 and 102 each include an illuminator module 104,which may include one or more LED arrays and accompanying LEDmodulators, a detector module 106, which may include one or more imagingarrays and accompanying photodiodes/amps, optics 105, and demodulatorsand data transmitters (not shown), which feed data to the EPM 103. TheEPM 103 comprises one or more field programmable gate arrays (“FPGAs”)301, one or more digital signal processors 303, and a communicationsprocessor 304. Modulation codes are generated inside the FPGA 301. Theintensity of each set of LEDs can be adjusted individually by way of adigital-to-analog converter (“DAC”) (not shown).

The FPGA 301 may also be accompanied by amplifiers (not shown) and ananalog-to-digital converter (“ADC”) 302 for the photodiode channelscontained on the detector modules 106. The FPGA 301 providesoversampling, filtering, and demodulation of the photodiode signals tomaximize the signal-to-noise ratio. The FPGA 301 receives the resultingdigital values and presents it to the DSP 303 in a format suitable forDSP access. The DSP 303 processes the data using embedded algorithms,such as discussed herein, and may make decisions based on pass/failcriteria and may authenticate the banknote 100. The communicationsprocessor 304 may gather results from the DSP 303 and format this datainto a message for output.

In embodiments of the present invention, as the banknote 100 travelsalong a note transport system (which are well-known in the art; see“Belt” and “Direction of Travel” in FIGS. 1 and 3), the illuminatormodule 104 may illuminate one or both sides of the note 100 with one ormore arrays of LEDs included in the illuminator module 104. Thescattered light may be captured by the photodiodes of the imaging arraysof the detector module(s) 106. A modulation of the LED wavelengths maybe implemented to enable the sensor device to separate the capturedimage into individual wavelength components. This results in amulti-spectral image stack of “multiple images,” which may be analyzedusing statistical methods, such as digital filtering and optimumstatistical detection, estimation, and classification (or “patternrecognition”) methods, or another analysis technique, such as principalcomponent analysis (“PCA”) to determine if the identifiedmulti-dimensional reflectance images fall within an acceptable range ofvariation for authentic banknotes, thereby validating the authenticityof the banknote 100. A statistical analysis of the multi-spectral imagestack may also be used to determine the denomination of the note basedon spatially separated regions of IR transparent inks and image elementsof the note. An example of such a multi-spectral image stack for theexample banknote of FIG. 2, imaged with multiple wavelengths isillustrated in FIG. 4. Each of the multiple images 1 . . . n representsan image captured from the light scattered by the banknote 100 at aparticular wavelength of light.

Referring again to FIG. 1, the illuminator module 104 may comprise anLED array that includes a plurality of different LEDs, which provide fora continuous illumination over a broad spectral range. One possiblespectral range of interest may be examined by spanning from theultraviolet to the near infrared by including LED wavelengths from 300nm to 1700 nm. The LEDs may vary in light wavelengths, by including two,three, or more different LEDs, each having different wavelengths.Example embodiments of the present invention are not limited to suchspectral ranges, but may be implemented with any number of wavelengthsand detectors of suitable spectral responses. Each pixel from each layerof the multi-spectral image stack (see FIG. 4) represents the intensityof light scattered from the surface of or transmitted through thebanknote 100 from a single illumination element. By collecting theintensity from the same spatial position from each layer of themulti-spectral stack, the spectral information is obtained as depictedin FIG. 5.

FIG. 7 further illustrates components of the illuminator module 104,according to example embodiments of the present invention. Theilluminator module 104 comprises a bank of LEDs positioned to projectlight onto the banknote 100 using a mirror and optical lens in optics105. The LEDs may project a plurality of different wavelengths. Thefirst bank of LEDs may project a shorter wavelength spectrum, and thesecond bank a higher wavelength spectrum. The LEDs may be modulatedusing DSSSM or TDM techniques, or any of the other techniques describedherein, allowing for simultaneous measurement of multiple wavelengths.

The illuminator module 104 comprises an illuminator substrate 802, asignal connector 803, and an array of LEDs 801 positioned to projectlight using the optics 105, which with respect to the illuminator module104 comprises a mirror 703 and two optical lenses 701 and 702. A holder704 and an aperture 703 may be also part of the illuminator module 104.When the bare LEDs 801 are powered, light passes through the lenses 701and/or 702. Light is then redirected onto the banknote 100 by the angledmirror 703 where it strikes the surface of the banknote 100 and isscattered back into the housing(s) 101 and/or 102, through the optics105 pertaining to the detector module 106, and onto the detector module106 (see also FIG. 1).

An enlarged view of the portion of the optics 105 controlling the lightfrom the illuminator module 104 is illustrated in FIG. 8. As light(represented in the figures as multiple beams) passes through the lenses702 and 701, the light strikes the mirror wedge 703 and is projectedonward to impinge upon the banknote 100. This configuration enables“mixing” of LED illumination for a relatively uniform line of light. Thelenses 701 and 702 collect and focus a large portion of the emittedlight from the LEDs, and project that light off of mirror 703 to imagethe array of emitted light upon the target. The cylindrical optics are“1D” optics in the sense that the light is collected and focused in onedirection (e.g., see the ray trace exiting out of lens 701), but allowthe LED light to spread out and propagate in an orthogonal direction.

Referring to FIG. 9, an example of an illuminator module 104 maycomprise a substrate comprising two rows of “n” number of bare LED dies801, with Row A comprising LEDs 1 . . . n, and Row B comprising LEDs n+1. . . m. Row A and Row B include LED wavelengths from two differentspectral regions. The LED array 801 may comprise an array of 12different wavelengths, a mixture of 7 in Row A that are imaged on onedetector array, and a mixture of 5 in Row B imaged on the seconddetector array. The different LEDs are identified by the wavelength oflight they produce. Separate versions of the illuminator modulesubstrate 802A and 802B are utilized for the lower sensor housing (LSH)101 and the upper sensor housing (USH) 102, respectively. One differencebetween the two versions may be that one is effectively a mirror imageof the other. For example, Row A and Row B of LED array 801A and thesignal connector 803 even-pin and odd-pin signals may be swapped (notethat LED 1 begins on the top of the illuminator module substrate 802A,and LED 1 begins on the bottom of the illuminator module substrate 802B)with respect to the LED array 801B.

FIG. 10 illustrates a similar view of the LED arrays 801A and 801B onsubstrates 802A and 802B, respectively, according to example embodimentsof the present invention. Referring to FIG. 10, the LEDs within each RowA and Row B may be evenly distributed in an interleaved pattern toprovide uniform, broad-band illumination across the width of thebanknote being examined. Each letter represents a different wavelength.This example shows a configuration where in Row A, 7 wavelengths arerepeated, while in Row B, 5 wavelengths are repeated. However, one couldutilize as many or few wavelengths in either row as needed. In thisexample, since there are 7 wavelengths in Row A and 5 in Row B, but thesame total number of LEDs in both, the wavelengths in Row B have morepopulation per wavelength then those in Row A. If there is a particularbanknote feature or set of wavelengths that are to be illuminatedbrightly, a row with fewer wavelengths (as few as a single wavelength)may be utilized to increase the intensity of that particular color.Likewise, a row where not all the wavelengths were evenly distributedmay be utilized, so a row like Row A, but where A=D and therefore thatwavelength is double the others. Thus, there would be a total of 7wavelengths with “A” being populated two times (“2×”) as much as theother 6.

Referring again to FIG. 1, each of the housings 101 and 102 may furtherinclude a multi-lens optical system (as further described herein) withinoptics 105 with a photodiode detector module 106, in accordance withexample embodiments of the present invention. The optical system focusesthe scattered light from the banknote 100 onto an array of photodiodeslocated within the detector module 106. The photodiodes convertscattered light to an electrical signal that is then used for imageprocessing by the EPM 103, such as to determine the location of certainbanknote features. There may be two separate bands of light being usedto examine the banknote 100. Short wavelengths may be focused onto onerow of photodiodes, and long wavelengths may be focused onto a secondrow of photodiodes. The light received from each pixel (location ofinterest) of the banknote 100 is focused onto a single photodiode.

FIG. 11 illustrates a photodiode arrangement of the detector module 106,according to example embodiments of the present invention. Referring toFIG. 11, an example of a detector module 106 may include a photodiodearray 1101 mounted on a substrate 1102, which includes a plurality ofphotodiode sensors PD1, PD2, . . . PD(n−1), PD(n) (first spectral row)and PD(n+1), PD(n+2), . . . PD(m−1), PD(m) (second spectral row). Inaddition to the sensors, associated trans-impedance amplifiers (notshown) may also be coupled to the sensors to convert the detected lightsignals to electrical voltage signals. The photodiode array 1101 may bearranged in two “spectral” rows of photodiodes. The first spectral rowmay be populated with silicon (Si) photodiodes for detecting shorterwavelength light, and the second spectral row may be populated withindium gallium arsenide (InGaAs) photodiodes for detecting longerwavelength light. However, other variations of photodiodes and similarsensors may be used to capture light used in the sensor detectionconfiguration. Additionally, a third row, or additional rows, mayfurther be added to detect yet other wavelengths of light received.

Referring again to FIG. 1, each sensor housing 101 and 102 may utilize aseparate version of the detector module 106. The lower sensor housing102 may comprise InGaAs photodiodes installed at photodiode locationsPD1−PD(n) of FIG. 11. Similarly, Si photodiodes may be installed atphotodiode locations PD(n+1)−PD(m) of FIG. 11. The upper sensor housing101 may reverse the order from the lower sensor housing 102, with Siphotodiodes installed at locations PD1−PD(n) and InGaAs photodiodesinstalled at locations PD(n+1)−PD(m). However, similar variations notshown in FIG. 11 may also be used to arrange the photodiodes.

FIG. 12 illustrates a spacing configuration for each spectral row of thephotodiode array 1101, according to example embodiments of the presentinvention. Referring to FIG. 12, each photodiode die 1201 has an “activearea” 1202 that is smaller than the physical die size 1201. Thephotodiodes used on the detector module 106 may have active areas thatare approximately 0.5 mm wide. Light falling outside the active area maynot be converted to an electrical signal, so if the photodiode dies 1201are placed adjacent to each other within a single row, the portion ofthe banknote 100 that falls between the active areas of adjacent die1201 will not be imaged. To alleviate this effect, the photodiodes 1201within a spectral row may be staggered (offset) as illustrated in FIG.12. The gaps 1203 between photodiode active areas along the lineperpendicular to the banknote travel may be effectively eliminated bythe offset layout of the photodiodes 1201.

FIG. 13 illustrates an example of the optics 105, according to exampleembodiments of the present invention. The optics 105 include theilluminator module 104, lenses 701, 702, and mirror 703, plus the lensassembly 1301 in the detector module 106. Exemplary light rays areillustrated to depict how the paths of light travel within the system.Optics 105 may include an optics barrel with a machined aluminum housing(not shown) for installation of a detector lens assembly 1301 withprecise external surface(s) that locate the lens assembly 1301 withinthe optical imaging device and provide the capability to focus theassembly for increased performance.

The detector lens assembly 1301 may comprise a relay lens optical systemthat images the target 100 (banknote) to the detector array 1101 with ahigh degree of light collection efficiency. The lens assembly 1301 maycontain an array of 5 individual lenses and 3 doublet lens assemblieswith anti-reflection coating for maximum transmission in the wavelengthregion. The set of lenses may be chosen to perform the reimaging acrossa wide range of wavelengths. Optical magnification may be selected basedon the resolution requirement for the banknote and the size of detectorelement. To resolve a feature size of 1 mm on the banknote and for adetector element of 0.5 mm×0.5 mm, a 0.5× optical magnification isutilized. As an example, if the lens assembly provides an optical powerof 0.5×, then each 1 mm×1 mm area on the banknote plane is imaged onto a0.5 mm×0.5 mm area on the detector array 1101 (0.5× means a 1 mm×1 mmarea on the banknote shows up as a 0.5 mm×0.5 mm area on the detectorplane).

FIG. 14 illustrates an optical system pictorial of a ray trace (raytracing is a method for calculating the path of waves or particlesthrough a system), according to example embodiments of the presentinvention. Referring to FIG. 14, details are illustrated five exemplarypaths of light contacting the banknote 100 and scattering backwardstowards the photodiode detector array 1101. Not all points of interestof the banknote 100 are illustrated in the ray trace of FIG. 14. Thebarrel casing is not shown in this drawing.

FIGS. 15 and 16 illustrate data processing on the raw banknote images(the multi-spectral data) collected by the detector module 106. FIG. 15illustrates steps performed by the FPGA 301 and DSPs 303, while FIG. 16provides a pictorial view of how the raw image data is organized by theFPGA 301. With reference to the previous examples for pixel resolutionand the number of illuminating wavelengths, two detectors measure theintensity of light for each pixel and generate 2048 readings, whichresults in 4096 readings per pixel.

The 4096 values of pixel data are received and fed into a FPGA 301 atoperation 1501. At operation 1502, the FPGA 301 takes the pixel data,and, using mathematical analysis for filtering and demodulation, amulti-wavelength spectrum is estimated, i.e., light intensities areestimated for each of the individual illumination wavelengths. The FPGA301 stores multi-spectral column data in an internal dual-port RAMgrouped into columns of multi-spectral pixels (i.e., 12 wavelengths) atoperation 1503. An interrupt is sent to the DSP 303 when each column iscompleted at operation 1504. The column data is received at DSP 303 atoperation 1505, and the data is re-organized and transformed atoperation 1506. The data is grouped into multiple monochromatic columnsat operation 1507, and the DSP 303 may run certain algorithms discussedherein to process the data at operation 1508.

Regarding the light measurements, the first part of a documentmeasurement may be a primary surface measurement employing a digitalsignal processing technique, such as direct sequence spread spectrummodulation (“DSSSM”) or time division multiplexing (“TDM”). Once the rawsignal of the primary surface measurement is processed in this manner,the image analysis algorithm may employ statistical analysis todetermine if any of the identified multi-dimensional reflectance imagesfalls within an acceptable range of variation for authentic banknotes.

The signal processing of the primary surface measurement relates to thecontrol (e.g., modulation) of the LED illuminators and the correspondinganalysis of the captured scattered light. This primary surfacemeasurement algorithm relies on the illuminator module 104 and thedetector module 106 in the optical front end of the sensor deviceinstrument. A succession of these measurements from each photodiode onthe array produces data from which a multi-spectral image may beconstructed. This algorithm produces the basic light measurement on aper pixel basis for each wavelength of LED. FIG. 4 illustrates thevarious different wavelength-based images generated for “n” wavelengths.

A primary surface measurement algorithm has certain performanceobjectives, such as, to allow multiple wavelength measurements from eachunfiltered photodiode and to provide high gain in the rawsignal-to-noise ratio (“SNR”). The algorithm allows simultaneousmeasurement of multiple wavelengths on unfiltered photodiodes by usingone of the aforementioned techniques. However, a limitation of manydetectors is their limited wavelength range of sensitivity.

For embodiments of the present invention, the sensor may be operated fordetection of wavelengths in a range of about 190 nm to 2600 nm range.Since single photodiodes with adequate quantum efficiency across thisband are not available, two types of photodiodes may be used. Forexample, silicon (Si) detectors have a sensitivity range fromapproximately 190 nm to 1100 nm, though this range can be slightlyvaried using different doping or coating strategies. Similarly, indiumgallium arsenide (InGaAs) detectors may be used, which have a spectralsensitivity from approximately 800 nm to 2600 nm, though this spectralrange can also be slightly varied using various strategies. For thedescribed embodiments, silicon (Si) photodiodes may be used for shorterwavelengths, and indium gallium arsenide (InGaAs) photodiodes may beused for longer wavelengths. The detector lens assembly 1301 may be usedto focus the scattered light from 1 mm square pixels across the width ofthe banknote 100 onto an array of photodiodes on the detector module.

The illuminator LED array 801 projects bands of broad-band light acrossthe banknote 100, and the scattered light is converted by an array ofphotodiodes 1101 into electrical signals that are processed, such as fordetecting authentication features. Photodiodes are broad-band detectorsand are not capable of determining the contribution of each of thewavelengths present in the broad-band illumination.

The illuminator LED arrays 801A, 801B may then comprise two rows of 168LEDs (see FIGS. 9 and 10). One row (e.g., Row A) may include LEDs of 7types, to operate as the illumination source for the Si photodiodearray. The other row (e.g., Row B) may include LEDs of 5 types, tooperate as the illumination source for the InGaAs photodiode array. Thedifferent types of LEDs in each row are interleaved to provide auniform-distribution broad-band light source (see FIG. 10).

To allow wavelength discrimination, the sensor may implement timedivision multiplexing (“TDM”). TDM processing may implement a rapidsequential illumination of the different LED wavelengths whilesimultaneously acquiring images with the detectors based on the sametime reference used for the original illumination modulation toessentially “freeze the note,” wherein the document (e.g., a banknote,or note) does not travel far between subsequent wavelengthilluminations. These acquisitions may be taken at speeds sufficient toeliminate significant spatial displacement between exposures. Such asequence of acquisitions may build a multi-spectral stack of images thatrepresents the same spatial features at each discrete wavelength.

FIG. 21 illustrates illumination bands and pixels that may be imaged bythe photodiode array 1101 overlaid on a banknote image. The photodiodes1201 are arranged in “staggered” rows due to the photodiode physicalpackage mounting constraints, as previously described with respect toFIG. 12. As the note travels across the face of the sensor, thephotodiodes image a given feature (pixel) in a time-shifted manner:

Si photodiodes in Column D image a feature at time=“N”

Si photodiodes in Column C image a feature at time=“N+200 microseconds”(e.g., corresponding to 2 mm of banknote travel time)

InGaAs photodiodes in Column B image a feature at time=“N+500microseconds” (e.g., corresponding to 5 mm of banknote travel time)

InGaAs photodiodes in Column A image a feature at time=“N+700microseconds” (e.g., corresponding to 7 mm of banknote travel time)

The FPGA 301 collects the digitized photodiode voltages and time-alignsthem to present coherent columns of pixel data to the DSP 303 for signalprocessing, as previously described.

Referring to FIG. 22, each LED wavelength may be assigned an orthogonaldigital code comprised of a sequence of 64 characters, where eachcharacter is a “0” or a “1.” Each character in the code represents aninterval of time, known as a “chip.” A given wavelength is turned onduring the chip time if the wavelength's code character for that chiptime is a “1.” The entire 64-bit code may be repeated for each 1 mm ofnote travel, which results in a chip equivalent to 1.56 microseconds(i.e., 64 chips occur during the 100 microseconds that it takes for thenote to advance 1 mm).

A unique code may be used for each of the 12 illumination wavelengths(though other numbers of wavelengths may be implemented) in the uppersensor housing (USH) 101 and the lower sensor housing (LSH) 102. Uniquecodes may be assigned to similar wavelengths in the upper and lowersensor housings to allow discrimination of back-scatter mode andtransmission mode wavelengths as detailed in the table shown in FIG. 22,which provides an example of codes assigned to the illumination wavelengths. For example, the code assigned to the 940 nm wavelength for theupper sensor housing (USH) 101 (channel 20) is different from the codeassigned to the 940 nm wavelength in the lower sensor housing (LSH) 102(channel 14).

Referring to FIG. 23, as the codes change from one chip to another, somenumber of LED wavelengths are turned on and others are turned off. Theoptical signal at the photodiode may increase or decrease on chipboundaries, depending on the number of wavelengths being turned on andoff and the absorption characteristics of the banknote surface. FIG. 23depicts four example wavelengths λ₁ . . . λ₄ through six chip intervalsand the resultant photodiode electrical signal, which is sent on to beprocessed by the EPM 103.

Referring to FIG. 24, each photodiode signal may be sampled by ananalog-to-digital converter (“ADC”) 32 times per chip interval. Theintensity value for the imaged pixel is calculated from the 32 samples,using an optimal estimation filter. Sampling each photodiode output 32times per chip interval and using 64 chips per pixel results inapproximately a 27 dB increase in signal-to-noise ratio.

With respect to DSSSM for use in wavelength discrimination, eachwavelength is assigned a unique code to simultaneously modulate all ofthe LEDs (all wavelengths) according to their respective codes, anddemodulate the resulting combined signal to recover the portion of thesignal due to each separate LED wavelength. (For TDM, each wavelength isassigned a different successive time slot, so that they are turned onone at a time.) The signal resulting from a given wavelength beingturned on is due to only that wavelength. Regardless of the modulationtechnique used, the entire sequence is repeated for each pixel worth ofnote travel (e.g., 1 m or 100 microseconds). For DSSSM, the codes may bea sequence of 32 or 64 “1's” and “0's” (on/off intervals). All 32 or 64of these intervals occur within the pixel time. (For TDM, all of thetime slots occur within the pixel time.)

DSSSM historically has been used by the U.S. military for lowprobability of intercepted communications, but in this application it isused to multiplex spectral data. Referring to FIG. 6, which shows an LEDarray of the illuminator module 104, the optics 105, and a photodiode ofthe imaging array detector module 106, the activation of each LED ismodulated using DSSSM modulation functions that are mutually orthogonal.This allows all of the LEDs to simultaneously interact with the surfaceunder test and thus produce light signals that are simultaneouslyreceived by each of the photodiodes while still allowing the signalsfrom each individual LED wavelength to be electronically separated fromthe others. In effect, this is a spectroscopic measurement that does notrequire filters or diffractive elements, of which wavelengths of lightfall onto each receiving detector (this is also true with respect toembodiments of the present invention utilizing TDM for this purpose). Inoperation, each source of light (e.g., LED) generates a differentwavelength λ₁, λ₂, λ₃, . . . λ₁₁, with a corresponding code, code 1,code 2, code 3, . . . code n. The “codes” are on/off LED currentmodulation functions, which may be represented as binary sequences,i.e., sequences of “0's” and “1's.” The codes are designed such thatthey have the same length (n), the same sum (n/2), and are mutuallyorthogonal, i.e., for any i, j, code(i)*code(j)=n/4. Because of theorthogonality of the codes, the combined light signal is demodulatedusing the same codes to obtain the portion of the combined signal due toeach separate LED wavelength.

By using the previously described modulation techniques, the wavelengthseparation is done electronically, and therefore it is not possible todetermine by physical examination of the instrument which wavelengthsout of the total set transmitted carry the information under test.Another benefit of this measurement technique is an extremeinsensitivity to fixed frequency interfering signals, such asfluorescent lamps or other flashing lights. Since the signal is spreadin frequency, and intersects with fixed frequency interferers over onlya narrow part of its frequency range, the system is relativelyinsensitive to fixed frequency noise sources. Furthermore, such analgorithm provides high gain in the processed SNR by using a relativelywide bandwidth system and taking many measurement cycles per pixel.

Referring again to FIG. 3, the DSP 303 reorganizes and transforms themulti-spectral pixel data to produce monochromatic and transformedcolumns in top-to-bottom, left-to-right order. Transmitted intensitiesare converted by taking logarithms. The DSP 303 appends columns to 2Dimage buffers, and performs filtering and normalization, producing 8-bitfiltered, normalized images for subsequent processing.

Example embodiments of the present invention may utilize algorithmsimplemented within the one or more DSPs 303 for the various recognitionand authentication processes. Document images may be obtained, analyzed,and searched to detect and authenticate expected features of thedocument. The quality of match between detected and expected features,such as location, intensity, and reflectance spectrum, may be determinedwhile compensating for various degrading effects such as soiling,wrinkling, translational, or rotational misalignment, etc., includingbanknotes that have material torn from or folded under each end. At eachpixel location of all or a portion of a banknote, light intensity may bemeasured at a plurality of wavelengths to provide more than one image ofa particular portion of the note.

The detection algorithms may process the data to determine certainfeatures, such as denomination, series, facing, and/or orientation bythe visible banknote image, denomination by IR transparent regions, ifpresent, authentication of features with unique spectral properties ifpresent, and/or multi-banknote events (1, 2, 3, or more overlaid notes).Verification of the previously listed requirements occurs regardless ofthe banknote series, flutter, tears, skew, and displacement.

Measurements taken over a large area of the note may be combined andaveraged. This reduces the errors caused by faded ink and colorvariations, and improves the signal-to-noise ratio. An improvedsignal-to-noise ratio allows for better quality of measurement andbetter predictability and reproducibility. Displacement, skewing, andmagnification may be compensated for by measuring the displacement andskew of each image and transforming and manipulating those images beforesubsequent processing. Flutter (displacement of the banknote in adirection generally not parallel with the direction of travel of thenote) may cause apparent note shortening and may be compensated for bynote magnification and scaling. Algorithms may be designed to allow forflutter by using a range of pixels in the corresponding images.Statistically, models used to measure features may compensate for alevel of deviation between a predefined template and the real banknote.The algorithms may also recognize and accommodate either an unrestrictedview of the surface of a banknote or a restricted view caused by machinetransport belts or other transport apparatus, which may partially blocka sensor housing's view of the surface of a banknote.

Raw pixel data may be interpreted and fed from the FPGA 301 into DSP303, where spectral processing (i.e., processing of intensity versuswavelength) is performed. Note that partitioning of the algorithmsbetween a plurality of DSPs 303 may be performed, (e.g., spatialinformation is processed (e.g., what inks are located where), andspectral information is processed (e.g., does the spectra of the inksmatch what is expected)), or partitioning between a plurality of DSPs303 may be performed by note. For example, each new note may be assignedto the next free DSP 303. Furthermore, processing may be performed by asingle DSP 303, as described in embodiments herein.

This multi-spectral data may be in single columns and re-organized andtransformed into a set of monochromatic columns, each of which isderived from an individual wavelength or from arbitrary combinations ofwavelengths. The reorganized, transformed image data is then used inspatial processing (i.e., processing of intensity vs. x, y spatiallocation). As columns of image data arrive, DSP 303 concatenates theminto rectangular images and then begins subsequent processing when apredetermined number of columns have been received. The spatialalgorithms are employed to determine denomination, facing, andorientation, to authenticate based on spectral features, and to sensemultiple overlaid notes. For example, the DSP 303 may process the dataand compare it against previously inputted templates of authentic and/orcounterfeit banknotes, which may have been scanned with the system tothereby input their respective characteristics, which are then comparedto a stream of actual banknotes to be examined. When this analysis hasbeen completed, the results are exported where codes are generated forexternal reporting 304.

Normalizing may be performed using a known model based on expectedintensity of the paper and dark ink (i.e., by monitoring itsreflectance). Normalization may be performed to compensate for fadedinks, soiled paper, operational differences between LEDs and/ordetectors, and associated amplifiers, etc. Normalization may requirecomparison operations based on well-known data stored in memory as abaseline for the expected image characteristics. For example, modelbanknote data may include various denominations and othercharacteristics of the note that are predefined and stored in a databasefor data processing and comparison purposes. The raw data extracted maybe processed and compared to the predefined note data.

The raw image data is analyzed to measure intensity distribution andspatial alignment, then translated, and scaled to normalize forsubsequent processing. More specifically, in the multi-spectral imagenormalization, images at each wavelength may be normalized by adaptivelyequalizing black and white levels. The black and white levels for eachwavelength may be adaptively estimated by an iterative method ofintensity histogram estimation. Offsets and gains are calculated basedon the measured black and white levels at each wavelength. Images arenormalized using calculated offsets and gains. Certain characteristicsmay be determined by the algorithms performed by the DSP 303, such asdenomination verification, feature recognition, orientation, faced ormiss-faced, and/or thickness.

As previously noted, the banknotes are transported through the sensordevice by a transport system of conveyance. The variability of thetransport system can introduce measurement variability into the imageacquisition, such as registration changes due to variable speed ofmotion. This variability may be compensated for by measuring andutilizing the speed of the transport in the time reference of the sensorto ensure proper image reconstruction.

Transports may also use belts or cables that potentially block the viewof one side of each note. Median characteristic responses of thedetectors are estimated and iteratively updated. Detectors obstructed bybelts are identified by significant deviation from median characteristicresponses. Pixels corresponding to obstructed detectors are eliminatedfrom consideration in further algorithms. Alternatively, obstructedpixels may be replaced by interpolation of neighboring visible pixels,where such data provides a useful basis to make subsequentauthentication decisions.

The denomination, series, facing, and orientation of each note may beidentified by locating and classifying multiple image features on eachside of the note. Notes may be accepted as authentic or rejected ascounterfeit by a classical statistical pattern detection andclassification method—essentially, a pattern recognition process inmultidimensional space. First, multiple physical features are locatedand classified by general size, shape, and location. Next, pixels withinthe perimeter of each feature are weighted by their probability of beingpart of that feature, based on spatial correlation with expected featureshape, and spectral correlation with expected ink color and density.Then, the cumulative mean spectrum of each physical feature is estimatedby combining the measured intensity of spatially and spectrally weightedpixels. Then, the spectrum vector may be augmented by appendingadditional metrics which are nonlinear functions of the spectrum. Suchfunctions may be chosen from a large parametric family by determiningoptimal parameters to maximize separation among classes and between mostsimilar class pairs. Next, the measured mean spectrum is classified by amaximum a-posteriori classifier, i.e., by combining probability densityfor each of multiple authentic and counterfeit spectral classes, priorexpected class probabilities, and conditional rejection based on aminimum probability constraint. An IR transparent region denominationfeature in the banknote may be detected, if present, and correlated withdenomination as determined from visible image features.

FIG. 17 illustrates a sensor device that detects multiple notes stacked1700 at the same time, according to example embodiments of the presentinvention. Referring to FIG. 17, the sensor device may detect and countmultiple stacked notes 1700 by measuring accumulated opticaltransmission loss. Light passing through single or multiple notes may beused to identify a presence of multiple stacked notes 1700. Thescattered light from the upper housing module 101 passes through eachnote and is captured by the lower housing 102 optics and vice versa,thereby identifying multi-note events, without being affected by changesin minute paper densities, such as the security thread and watermark.Note, the dashed line represents light traveling from the upper sensorhousing 101 to the lower sensor housing 102 and the dotted linerepresents light traveling from the lower sensor housing 102 to theupper sensor housing 101.

For example, stacked note detection may be achieved using a“transmission mode imaging” of the authentication optical system. Inthis mode of operation, approximately 10% of the light from the uppersensor housing 101 illuminator LED array 104 passes through the banknoteand is scattered off the lower surface of the note. Similarly 10% of thelight from the lower sensor housing 102 passes through the banknote andis scattered off the upper surface of the note. The upper and lowerhousing photodiode imaging arrays 106 and associated electronics measurethe amount of light transmitted through the note and determines whetherthe banknote has the attenuation characteristics of a single note, twostacked notes, or more than two stacked notes. The transmission imagecollected by each sensor can also be a multi-spectral stack oftwo-dimensional images of the note.

Each pixel layer of the stack represents the intensity of a singlewavelength of light remaining after it passes through the note.Alternatively, all wavelengths of the LED array may be turned on in anycombination or simultaneously to create transmission signals of higherintensity but reduced spectral resolution. Sacrifice of spectralresolution for increased signal can be very advantageous in measurementsof properties of limited spectral interest and low transmission, such asfound in banknote thickness determinations over white or black areas.

The operations of a method or algorithm described in connection with theembodiments disclosed herein may be embodied directly in hardware, in acomputer program executed by a processor, or in a combination of thetwo. A computer program may be embodied on a computer readable medium,such as a storage medium. For example, a computer program may reside inrandom access memory (“RAM”), flash memory, read-only memory (“ROM”),erasable programmable read-only memory (“EPROM”), electrically erasableprogrammable read-only memory (“EEPROM”), registers, hard disk, aremovable disk, a compact disk read-only memory (“CD-ROM”), or any otherform of storage medium known in the art.

An exemplary storage medium may be coupled to the processor such thatthe processor may read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anapplication specific integrated circuit (“ASIC”). In the alternative,the processor and the storage medium may reside as discrete components.For example, FIG. 19 illustrates an example network element 1900, whichmay represent any of the above-described components of the previousdrawings. A memory 1910 and a processor 1920 may be discrete componentsof the network entity 1900 that are used to execute an application orset of operations. The application may be coded in software in acomputer language understood by the processor 1920, and stored in acomputer readable medium, such as the memory 1910. The computer readablemedium may be a non-transitory computer readable medium that includestangible hardware components in addition to software stored in memory.Furthermore, a software module 1930 may be another discrete entity thatis part of the network entity 1900, and which contains softwareinstructions that may be executed by the processor 1920. In addition tothe above noted components of the network entity 1900, the networkentity 1900 may also have a transmitter and receiver pair configured toreceive and transmit communication signals (not shown).

An example method of producing multi-spectral imaging of a plurality ofline scan elements is disclosed. The method may include producing lightvia at least one illumination module at operation 2001, comprising anarray of light sources configured to produce light at a plurality ofdifferent wavelengths. The method may also include creating a uniformline of illumination with each of the different wavelengths produced bythe at least one illumination module, at operation 2002, and detectinglight produced by the at least one illumination module via at least onedetection module at operation 2003.

While embodiments of the present invention have been described, it is tobe understood that the embodiments described are illustrative only, andthe scope of the invention is to be defined solely by the appendedclaims when considered with a full range of equivalents andmodifications (e.g., protocols, hardware devices, software platforms,etc.) thereto.

What is claimed is:
 1. A method for authenticating an object,comprising: modulating a plurality of wavelengths of light from aplurality of light-emitting sources, wherein modulating the plurality ofwavelengths of light illuminates the object; detecting a light signalfrom the illuminated object with a plurality of photodiodes; producing areflectance spectrum from the light signal; comparing the reflectancespectrum to a template reflectance spectrum of an authentic object; anddetermining if the illuminated object is authentic as a function of thecomparison.
 2. The method of claim 1, wherein producing the reflectancespectrum comprises demodulating the light signal.
 3. The method of claim1, wherein modulating the plurality of wavelengths of light comprisesemploying a time division multiplexing (TDM).
 4. The method of claim 1,wherein modulating the plurality of wavelengths of light comprisesemploying a direct sequence spread spectrum modulation (DSSM).
 5. Themethod of claim 1, wherein producing the reflectance spectrum comprisesgenerating a multi-spectrum image of at least a specified portion of theilluminated object.
 6. The method of claim 5, wherein the multi-spectrumimage comprises a plurality of images of the specific portion of theilluminated object associated with one or more of the plurality ofwavelengths of light.
 7. The method of claim 1, wherein modulating theplurality of wavelengths of light comprises using a plurality oforthogonal sequence codes.
 8. The method of claim 7, wherein producingthe reflectance spectrum comprises demodulating the light signal usingthe plurality of orthogonal sequence codes.
 9. The method of claim 1,wherein the reflectance spectrum comprises one or more intensity levelsassociated with one or more of the plurality of wavelengths of light.10. A method for authenticating an object, comprising: illuminating theobject with a plurality of wavelengths of light from a plurality oflight-emitting sources, wherein illuminating the object comprisesmodulating the light-emitting sources; detecting light scattered fromthe illuminated object with a plurality of photodiodes to create amulti-spectrum image of at least a specified portion of the illuminatedobject, wherein the multi-spectrum image comprises a plurality of imagesassociated with one or more of the plurality of wavelengths; comparingthe multi-spectrum image to a template multi-spectrum image of anauthentic object; and determining if the illuminated object is authenticbased on the comparison.
 11. The method of claim 10, wherein theplurality of light-emitting sources and the plurality of photodiodes areoptically coupled such that the plurality of wavelengths of light aresimultaneously directed to the plurality of photodiodes.
 12. The methodof claim 10, wherein detecting the light scattered from the illuminatedobject comprises producing a reflectance spectrum for the detectedscattered light.
 13. The method of claim 10, wherein the illuminating isperformed as a line scan illumination of the object, wherein the linescan illumination is performed as the object moves past the plurality oflight-emitting sources.
 14. The method of claim 10, wherein theplurality of light-emitting sources and the plurality of photodiodes areoptically coupled via a multi-lens optical system, and wherein themulti-lens optical system comprises a detector lens assembly configuredto collect the light scatted from the illuminated object and direct thecollected light onto the plurality of photodiodes.
 15. An apparatus forauthenticating an object comprising: a memory; a processor coupled tothe memory, wherein the memory comprises computer executableinstructions stored on a non-transitory computer readable medium suchthat when executed by the processor causes the processor to: modulate aplurality of wavelengths of light from a plurality of light-emittingsources, wherein modulating the plurality of wavelengths of lightilluminates the object; detect a light signal from the illuminatedobject with a plurality of photodiodes; produce a reflectance spectrumfrom the light signal; compare the reflectance spectrum to a templatereflectance spectrum of an authentic object; and determine if theilluminated object is authentic as a function of the comparison.
 16. Theapparatus of claim 15, wherein producing the reflectance spectrumcomprises demodulating the light signal.
 17. The apparatus of claim 15,wherein modulating the plurality of wavelengths of light comprisesemploying a time division multiplexing (TDM).
 18. The apparatus of claim15, wherein modulating the plurality of wavelengths of light comprisesemploying a direct sequence spread spectrum modulation (DSSM).
 19. Theapparatus of claim 15, wherein producing the reflectance spectrumcomprises generating a multi-spectrum image of at least a specifiedportion of the illuminated object, and wherein the multi-spectrum imagecomprises a plurality of images of the specific portion of theilluminated object associated with one or more of the plurality ofwavelengths of light.
 20. The apparatus of claim 15, wherein modulatingthe plurality of wavelengths of light comprises using a plurality oforthogonal sequence codes, and wherein producing the reflectancespectrum comprises demodulating the light signal using the plurality oforthogonal sequence codes.